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author | Ricardo Wurmus <rekado@elephly.net> | 2020-03-02 23:02:54 +0100 |
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committer | Ricardo Wurmus <rekado@elephly.net> | 2020-03-02 23:05:49 +0100 |
commit | 11ab52888d416d9fcf33349b1f376f7e47f4cdff (patch) | |
tree | 72aebb47533e70d1872d8d39b2ca5bb63185506a /gnu/packages | |
parent | 505d6716d0df1dc5e8ef3438f0d7ec68c695d874 (diff) | |
download | guix-patches-11ab52888d416d9fcf33349b1f376f7e47f4cdff.tar guix-patches-11ab52888d416d9fcf33349b1f376f7e47f4cdff.tar.gz |
gnu: Add r-zvcv.
* gnu/packages/cran.scm (r-zvcv): New variable.
Diffstat (limited to 'gnu/packages')
-rw-r--r-- | gnu/packages/cran.scm | 34 |
1 files changed, 34 insertions, 0 deletions
diff --git a/gnu/packages/cran.scm b/gnu/packages/cran.scm index 7bc85106b3..87d0eb81e0 100644 --- a/gnu/packages/cran.scm +++ b/gnu/packages/cran.scm @@ -20603,3 +20603,37 @@ method (Sen, 1968) plus implementation of Xuebin Zhang's (Zhang, 1999) and Yue-Pilon's (Yue, 2002) pre-whitening approaches to determining trends in climate data.") (license license:lgpl2.1))) + +(define-public r-zvcv + (package + (name "r-zvcv") + (version "1.0.0") + (source + (origin + (method url-fetch) + (uri (cran-uri "ZVCV" version)) + (sha256 + (base32 + "1npw836q2skx54843lgxvb0rfwafckjc8k8dljykm60ad3z7zak8")))) + (properties `((upstream-name . "ZVCV"))) + (build-system r-build-system) + (propagated-inputs + `(("r-abind" ,r-abind) + ("r-glmnet" ,r-glmnet) + ("r-mvtnorm" ,r-mvtnorm) + ("r-partitions" ,r-partitions) + ("r-rcpp" ,r-rcpp) + ("r-rcpparmadillo" ,r-rcpparmadillo))) + (home-page "https://cran.r-project.org/web/packages/ZVCV/") + (synopsis "Zero-Variance Control Variates") + (description + "@dfn{Zero-variance control variates} (ZV-CV) is a post-processing method +to reduce the variance of Monte Carlo estimators of expectations using the +derivatives of the log target. Once the derivatives are available, the only +additional computational effort is in solving a linear regression problem. +This method has been extended to higher dimensions using regularisation. This +package can be used to easily perform ZV-CV or regularised ZV-CV when a set of +samples, derivatives and function evaluations are available. Additional +functions for applying ZV-CV to two estimators for the normalising constant of +the posterior distribution in Bayesian statistics are also supplied.") + (license license:gpl2+))) |